Classification of heart arrhythmia is an important step in developing devices for monitoring the health of individuals. This paper proposes a three module system for classification of electrocardiogram (ECG) beats. These modules are: denoising module, feature extraction module and a classification module. In the first module the stationary wavelet transform (SWF) is used for noise reduction of ...

It is one of the topics that have been studied extensively on maximum power point tracking (MPPT) recently. Traditional or soft computing methods are used for MPPT. Since approaches more effective than traditional approaches, studies MPPT shifted in this direction. This study aims comparison performance seven meta-heuristic training algorithms neuro-fuzzy The particle swarm optimization (PSO), ...

Recently, neural networks have been widely applied for solving partial differential equations (PDEs). Although such methods proven remarkably successful on practical engineering problems, they not shown, theoretically or empirically, to converge the underlying PDE solution with arbitrarily high accuracy. The primary difficulty lies in highly non-convex optimization problems resulting from netwo...

cerebellar model articulation controller neural network is a computational model of cerebellum which acts as a lookup table. the advantages of cmac are fast learning convergence, and capability of mapping nonlinear functions due to its local generalization of weight updating, single structure and easy processing. in the training phase, the disadvantage of some cmac models is unstable phenomenon...

Batch training algorithms with a di erent learning rate for each weight are investigated. The adaptive learning rate algorithms of this class that apply inexact one{ dimensional subminimization are analyzed and their global convergence is studied. Simulations are conducted to evaluate the convergence behavior of two training algorithms of this class and to compare them with several popular trai...